In this paper we deal with the above problems by extending the BERT model to explicitly model sentence representations. This is realized by distilling the sentence representations from the output of the BERT block and aggregating the representations of the tokens that make a sentence. Secondly, once we have the sentence representations, we apply a Dynamic Memory Network [1]}, [2]} to model sentence-wise relations for relevance estimation. We are interested in the following research questions:
